Fit for purpose?

Overview:

Climate risks, such as those associated with increased intensity of precipitation events and sustained changes in extreme temperatures, are factors facing many organizations and individuals with responsibilities for planning decisions on decadal or longer timescales. Risks from a changing climate often are assessed using outputs from Global Climate Models (GCMs), which are bias corrected and downscaled using a plethora of methods, resulting in a potentially paralyzing amount of data. Presented with so many choices of downscaled climate data products that potentially could be used as input to a given climate impacts study, a reasonable question to ask is “Which methods are fit for purpose?”  Unfortunately, there is no one-size-fits-all answer to that question, because of the wide variety of downscaling methods (each with its own performance characteristics) -and- the wide variety of risks that can be considered (each with its own sensitivities to weather and climate factors.)

Our multi-institutional research team consists of accomplished downscaling method developers (statistical, hybrid, and dynamical) and experienced climate system analysts (observations and models.) To address the “Fit for purpose” question, we aim to develop meaningful, objective tests and integrated interpretations to discriminate between downscaling methods.  Our evaluations will include diagnostic measures related to a range of environmental factors (e.g., water resources, heat and health, ecosystem stressors), with additional focus on those of particular interest for select infrastructure applications in the United States. Goals of this project include developing knowledge that will enable risk managers to make better informed decisions on strategic adaptation planning in the face of uncertain climate change impacts, and  communicating that knowledge in multiple ways.  In other words, we seek to develop information and knowledge that can be translated into guidance, so as to better enable practitioners to answer the question of whether, and to what extent, a particular downscaled climate projection data product is “fit for purpose” for a given decision-relevant application.

The postdoc position:

The person selected for this postdoc position will be a member of a multi-institutional project team, and will coordinate their research activities with the team’s investigators at NOAA/GFDL, NCAR, Cornell Univ. and Mitre.org.  Though this post-doc position is linked to NOAA/GFDL, we will consider remote work or hybrid remote/on-site options. 

The postdoctoral researcher will have the opportunity to develop actionable climate data and knowledge that will be used directly by applied researchers and stakeholders interested in climate adaptation and resiliency.  They will conduct independent and collaborative research to identify the strengths and weaknesses of the different downscaled climate projection data products that have been generated for the United States for the purpose of applied climate research.  Work will be focused on identifying the unique characteristic of each dataset, investigating the role of downscaling methodological assumptions on dataset fidelity, and developing a framework for evaluation that can be applied to existing and future downscaled products. A key component of this work will be communicating the results of this work to an interdisciplinary audience interested in understanding which data products are “fit for purpose” for specific applications of interest.

Consistent with the theme of this project, several research team members participated in the November 2023 workshop
Understanding Decision-Relevant Regional Climate Projections Workshop
including as speakers and as part of the workshop’s science organizing committee.